Performance environnementale et mesure de la productivité
AbstractThe study results presented here are derived from a process whose purpose was the initial deployment and use of the data envelopment analysis techniques and linear programming in R environment to verify the feasibility of transferring tools supporting analyzes conducted after the project Luxklems. The results and their theoretical subtended are presented in brief but show the possibilities and flexibility offered by the R environment to treat optimization problems. The focus is on the evolution of the Malmquist index when considering the undesirable outputs and also seeks to compare the results with and without consideration of environmental performance in in theoretical and empirical exercise covering 15 European countries and the United States. This approach uses for purposes of calculation, the strengths of the R language and some packages dealing with linear programming and directional distance functions. Thus, programs have been developed and adapted to extend the measurement of total factor productivity and its components - technical progress and technical efficiency – to take in account the environmental performance by minimizing infeasibility problems encountered in the usual approaches using Malmquist indices. Indeed, faced with the need to take into account the effects of production on the environment and more generally the urgency to find the path of sustainable development, many attempts have been made to reinforce measures productivity growth including the negative impact of pollution that the production of goods and services generates.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 41456.
Date of creation: 20 Sep 2012
Date of revision:
Environmental performance; Data envelopment analysis (DEA); Undesirable output; Return to scale; Sequential Malmquist-Luenberger index; Malmquist-Luenberger index;
Find related papers by JEL classification:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
This paper has been announced in the following NEP Reports:
- NEP-AGR-2012-12-10 (Agricultural Economics)
- NEP-ALL-2012-12-10 (All new papers)
- NEP-EFF-2012-12-10 (Efficiency & Productivity)
- NEP-ENV-2012-12-10 (Environmental Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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